1. Technical Field
This invention relates generally to the field of electronic discovery. More specifically, this invention relates to predicting the cost of electronic discovery.
2. Description of the Related Art
Electronic discovery, also referred to as e-discovery or EDiscovery, concerns electronic formats that are discovered as part of civil litigations, government investigations, or criminal proceedings. In this context, the electronic form is anything that is stored on a computer-readable medium. Electronic information is different from paper information because of its intangible form, volume, transience, and persistence. In addition, electronic information is usually accompanied by metadata, which is rarely present in paper information. Electronic discovery poses new challenges and opportunities for attorneys, their clients, technical advisors, and the courts, as electronic information is collected, reviewed, and produced.
The electronic discovery process focuses on collection data from people that have knowledge about the pending litigation and the data sources that they control. These people are referred to as custodians. The data sources include work computers, home computers, mobile devices, etc. The cost of collecting data from a variety of custodians controlling a variety of data sources varies according to different parameters. Thus, there is a need for an electronic discovery system that accurately predicts the costs.
A number of electronic discovery systems provide simple calculator sheets that allow a user to enter volume and cost parameters to estimate the potential discovery cost for one matter. These tools vary in the depth and breadth of their model, and the cost equation parameters they offer, but they all lack several features. They fail to provide a means for aggregating facts in a scalable, reliable and repeatable manner. They also fail to calculate historic trend models or profiles. While they enable the user to provide input into the model and to perform scenario analysis, they cannot combine automated forecast and user feedback. As a result, parameters and relationships between parameters that are not explicitly integrated in the cost model must be manually input by the user.
The electronic discovery systems also fail to include any subjective assessment of the degree of advancement of the matter in its lifecycle, which means that any such assessment or input must be factored in by the user into all of the other input parameters. Manually inputting those parameters is so complex and time consuming that it can offset any advantages to be gained from the system.
The electronic discovery systems provide a cost equation model that is rigid and cannot easily be configured to adapt to the specific context of the customer. They do not provide any facility to aggregate cost across multiple matters, or perform analytics on the overall matter portfolio. They do not have any capability to integrate the specific nature and cost profile of an individual custodian or data source as part of the cost forecast. As a result, current electronic discovery tools are limited in application and accuracy.